In any video communication solution, a challenge is to simultaneously optimize resource utilization and perceptual quality. In a remote management video access scenario, perceptual quality includes sharp edges of fonts, gradients in application program menus and low latency between video requests and responses. The increase in video resolutions in recent years poses additional bandwidth requirements; if not addressed with appropriate combination of compression and video reconstruction approaches, the quality of video may become unusable in a remote access scenario due to the nature of artifacts introduced. In order to mitigate the effect on the perceptual quality of the video due to these artifacts, the received video needs to be processed fast enough such that the human eye cannot recognize the removal of noise embedded within the video. The need for video processing and rendering at higher resolutions necessitate new noise reduction algorithms that are efficient both in memory size as well as in time.
In remote management systems, video data is transmitted from a remote device or target through a keyboard, video, mouse (KVM) switch to a user that may be located remotely or locally to the KVM switch. In a typical KVM over IP system, source video is sampled from incoming analog VGA signals, and reduced from 24 bits to 16 bits. In particular, the received stream is originally sampled via an A/D device and reduced in bit depth from its original source. As a consequence, down-sampling noise is prominently visible with existing KVM over IP switches.
In particular, perceptual artifacts in the reconstructed video stream originate from a number of channel degradation factors including any or all of the following: (1) reduced color depth or sub-sampled source; (2) channel interference in switched video transmission; or (3) low-contrast transition effects in the video content (a common trend in recent operating systems that imposes additional constraints on bandwidth/quality).
Existing solutions may use video smoothing methods on the source or server side (target) but still result in rendered video with perceptual quality problems and may not satisfy the requirements for real time applications. Further, a KVM over IP implementation that downsamples the incoming video to 16 bits or less has limited ability to exploit a server side solution due to the difficulty of preserving the effects of the video processing using 16 bits. Finally, such systems cannot cost-effectively counteract the noise and other degradations on the source information within the time constraints of a real time video session. The perceptual quality of the noisy received video data needs to be improved.